#ai-agents — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #ai-agents, aggregated by home.social.
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Currently juggling work with 2 AI agents + 3 dev teams.
I give devs the simple stuff. The hard stuff? Me + my agent. 24/7. No sleep, no "I'll do it tomorrow", no context lost.
Agents remember everything, need zero handholding, and just ship. I don't explain better to humans — I just get more done with AI.
If devs don't adapt soon, I'll stop hiring them. Performance-wise, agents already win. Faster. Cleaner. Done.
The future is already here, just unevenly distributed.
#AIagents...
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Honestly? I've been juggling 2 AI agents + 3 dev teams lately. The pattern is clear: devs get the easy stuff, agents get the hard stuff. Not because I can't explain it—because the agent delivers at 3am, never forgets context, and just... does it. No monitoring needed. If dev teams don't adapt their workflow soon, I won't need them at all. The performance gap is too big. 🚀 #AIagents #FutureOfWork #DevLife
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Most people who say they want an agent want a process that decomposes a job, runs steps in order, checks state, and produces an audit trail. That is orchestration, solved for twenty years. The model is a step inside it, not the thing running it.
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Most people who say they want an agent want a process that decomposes a job, runs steps in order, checks state, and produces an audit trail. That is orchestration, solved for twenty years. The model is a step inside it, not the thing running it.
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Most people who say they want an agent want a process that decomposes a job, runs steps in order, checks state, and produces an audit trail. That is orchestration, solved for twenty years. The model is a step inside it, not the thing running it.
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Most people who say they want an agent want a process that decomposes a job, runs steps in order, checks state, and produces an audit trail. That is orchestration, solved for twenty years. The model is a step inside it, not the thing running it.
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Most people who say they want an agent want a process that decomposes a job, runs steps in order, checks state, and produces an audit trail. That is orchestration, solved for twenty years. The model is a step inside it, not the thing running it.
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https://www.europesays.com/people/204787/ Meta Backs Off Plan to Replace Staff With AI #AI #AIAgents #Automation #layoffs #MarkZuckerberg #Meta
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Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.
#CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec
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Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.
#CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec
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Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.
#CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec
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Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.
#CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec
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Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.
#CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec
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Real talk: I delegate simple tasks to dev teams and handle the hard stuff with AI agents. Why? Not because I can't explain it — agents are just faster, available 24/7, and never half-ass a task. They don't need hand-holding. Honestly, if devs don't adapt, I'll stop working with them altogether. AI wins on performance, speed, and quality. Period. 🚀
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"Documentation files on more than 100 websites are referencing potentially dangerous executable content that gets installed automatically when visited by many AI agents. A few dozen companies, some of them Fortune 500s, are among those that executed proof-of-concept code. At least one misconfigured site is directing visitors, human or AI, to live malware.
The potentially dangerous content is in llms.txt and llms-full.txt files, an emerging convention websites employ to provide machine-readable summaries of the site’s content and its high-level structure. These files are the AI equivalent of the robots.txt standard that instructs search engines how to index the site’s content. Google Lighthouse, a tool for helping web developers, has more here. Correctly configured llms.txt and llms-full.txt files for Cloudflare are here and here.
Researchers at a stealth startup in Israel scanned 6,214 live domains belonging to defense contractors, Fortune 500, and Big Tech companies. Of the 8,265 llms.txt and llms-full.txt files they found (many sites hosted both an llms.txt and an llms-full.txt file), 120 of them, each on a different site, pointed to one or more code packages or domain names that weren’t registered. To test what happens when an AI agent processes such files, the researchers registered a handful of the unclaimed names and hosted packages that caused any machine executing them to reach out to their server. Within an hour, the researchers received a phone-home response from a Fortune 500 company. Over time, they got a few dozen more, some from more Fortune 500 companies and others from startups. Their beacon also recorded the chain of parent processes that spawned each install, ultimately revealing that coding agents, including Claude, OpenAI’s Codex, and Nous Research’s Hermes, were involved."
#AI #CyberSecurity #LLMs #AIAgents #AgenticAI #Codex #Claude #Hermes #Anthropic #OpenAI #NousResearch
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"Documentation files on more than 100 websites are referencing potentially dangerous executable content that gets installed automatically when visited by many AI agents. A few dozen companies, some of them Fortune 500s, are among those that executed proof-of-concept code. At least one misconfigured site is directing visitors, human or AI, to live malware.
The potentially dangerous content is in llms.txt and llms-full.txt files, an emerging convention websites employ to provide machine-readable summaries of the site’s content and its high-level structure. These files are the AI equivalent of the robots.txt standard that instructs search engines how to index the site’s content. Google Lighthouse, a tool for helping web developers, has more here. Correctly configured llms.txt and llms-full.txt files for Cloudflare are here and here.
Researchers at a stealth startup in Israel scanned 6,214 live domains belonging to defense contractors, Fortune 500, and Big Tech companies. Of the 8,265 llms.txt and llms-full.txt files they found (many sites hosted both an llms.txt and an llms-full.txt file), 120 of them, each on a different site, pointed to one or more code packages or domain names that weren’t registered. To test what happens when an AI agent processes such files, the researchers registered a handful of the unclaimed names and hosted packages that caused any machine executing them to reach out to their server. Within an hour, the researchers received a phone-home response from a Fortune 500 company. Over time, they got a few dozen more, some from more Fortune 500 companies and others from startups. Their beacon also recorded the chain of parent processes that spawned each install, ultimately revealing that coding agents, including Claude, OpenAI’s Codex, and Nous Research’s Hermes, were involved."
#AI #CyberSecurity #LLMs #AIAgents #AgenticAI #Codex #Claude #Hermes #Anthropic #OpenAI #NousResearch
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"Documentation files on more than 100 websites are referencing potentially dangerous executable content that gets installed automatically when visited by many AI agents. A few dozen companies, some of them Fortune 500s, are among those that executed proof-of-concept code. At least one misconfigured site is directing visitors, human or AI, to live malware.
The potentially dangerous content is in llms.txt and llms-full.txt files, an emerging convention websites employ to provide machine-readable summaries of the site’s content and its high-level structure. These files are the AI equivalent of the robots.txt standard that instructs search engines how to index the site’s content. Google Lighthouse, a tool for helping web developers, has more here. Correctly configured llms.txt and llms-full.txt files for Cloudflare are here and here.
Researchers at a stealth startup in Israel scanned 6,214 live domains belonging to defense contractors, Fortune 500, and Big Tech companies. Of the 8,265 llms.txt and llms-full.txt files they found (many sites hosted both an llms.txt and an llms-full.txt file), 120 of them, each on a different site, pointed to one or more code packages or domain names that weren’t registered. To test what happens when an AI agent processes such files, the researchers registered a handful of the unclaimed names and hosted packages that caused any machine executing them to reach out to their server. Within an hour, the researchers received a phone-home response from a Fortune 500 company. Over time, they got a few dozen more, some from more Fortune 500 companies and others from startups. Their beacon also recorded the chain of parent processes that spawned each install, ultimately revealing that coding agents, including Claude, OpenAI’s Codex, and Nous Research’s Hermes, were involved."
#AI #CyberSecurity #LLMs #AIAgents #AgenticAI #Codex #Claude #Hermes #Anthropic #OpenAI #NousResearch
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"Documentation files on more than 100 websites are referencing potentially dangerous executable content that gets installed automatically when visited by many AI agents. A few dozen companies, some of them Fortune 500s, are among those that executed proof-of-concept code. At least one misconfigured site is directing visitors, human or AI, to live malware.
The potentially dangerous content is in llms.txt and llms-full.txt files, an emerging convention websites employ to provide machine-readable summaries of the site’s content and its high-level structure. These files are the AI equivalent of the robots.txt standard that instructs search engines how to index the site’s content. Google Lighthouse, a tool for helping web developers, has more here. Correctly configured llms.txt and llms-full.txt files for Cloudflare are here and here.
Researchers at a stealth startup in Israel scanned 6,214 live domains belonging to defense contractors, Fortune 500, and Big Tech companies. Of the 8,265 llms.txt and llms-full.txt files they found (many sites hosted both an llms.txt and an llms-full.txt file), 120 of them, each on a different site, pointed to one or more code packages or domain names that weren’t registered. To test what happens when an AI agent processes such files, the researchers registered a handful of the unclaimed names and hosted packages that caused any machine executing them to reach out to their server. Within an hour, the researchers received a phone-home response from a Fortune 500 company. Over time, they got a few dozen more, some from more Fortune 500 companies and others from startups. Their beacon also recorded the chain of parent processes that spawned each install, ultimately revealing that coding agents, including Claude, OpenAI’s Codex, and Nous Research’s Hermes, were involved."
#AI #CyberSecurity #LLMs #AIAgents #AgenticAI #Codex #Claude #Hermes #Anthropic #OpenAI #NousResearch
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"Documentation files on more than 100 websites are referencing potentially dangerous executable content that gets installed automatically when visited by many AI agents. A few dozen companies, some of them Fortune 500s, are among those that executed proof-of-concept code. At least one misconfigured site is directing visitors, human or AI, to live malware.
The potentially dangerous content is in llms.txt and llms-full.txt files, an emerging convention websites employ to provide machine-readable summaries of the site’s content and its high-level structure. These files are the AI equivalent of the robots.txt standard that instructs search engines how to index the site’s content. Google Lighthouse, a tool for helping web developers, has more here. Correctly configured llms.txt and llms-full.txt files for Cloudflare are here and here.
Researchers at a stealth startup in Israel scanned 6,214 live domains belonging to defense contractors, Fortune 500, and Big Tech companies. Of the 8,265 llms.txt and llms-full.txt files they found (many sites hosted both an llms.txt and an llms-full.txt file), 120 of them, each on a different site, pointed to one or more code packages or domain names that weren’t registered. To test what happens when an AI agent processes such files, the researchers registered a handful of the unclaimed names and hosted packages that caused any machine executing them to reach out to their server. Within an hour, the researchers received a phone-home response from a Fortune 500 company. Over time, they got a few dozen more, some from more Fortune 500 companies and others from startups. Their beacon also recorded the chain of parent processes that spawned each install, ultimately revealing that coding agents, including Claude, OpenAI’s Codex, and Nous Research’s Hermes, were involved."
#AI #CyberSecurity #LLMs #AIAgents #AgenticAI #Codex #Claude #Hermes #Anthropic #OpenAI #NousResearch
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"Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.
Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.
Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."
#AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI
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"Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.
Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.
Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."
#AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI
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"Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.
Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.
Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."
#AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI
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"Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.
Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.
Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."
#AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI
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"Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.
Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.
Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."
#AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI
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ICYMI: Explaining OKF: OKF, the Open Knowledge Format, is Google Cloud's open markdown specification for packaging the organizational knowledge that AI agents read before they act. https://ppc.land/okf/ #OKF #OpenKnowledgeFormat #GoogleCloud #AIAgents #KnowledgeManagement
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ICYMI: Explaining OKF: OKF, the Open Knowledge Format, is Google Cloud's open markdown specification for packaging the organizational knowledge that AI agents read before they act. https://ppc.land/okf/ #OKF #OpenKnowledgeFormat #GoogleCloud #AIAgents #KnowledgeManagement
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ICYMI: Explaining OKF: OKF, the Open Knowledge Format, is Google Cloud's open markdown specification for packaging the organizational knowledge that AI agents read before they act. https://ppc.land/okf/ #OKF #OpenKnowledgeFormat #GoogleCloud #AIAgents #KnowledgeManagement
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Two AI agents + three dev teams. I give the simple stuff to humans, keep the hard stuff for the agent. Not because I can't explain it — agents are just faster, work 24/7, remember everything, and need zero hand-holding. My devs? Limited hours, variable skills, constant oversight. Honestly, if devs don't adapt soon, I'll just stop working with them. AI wins on perf, speed, and quality. Period. 🚀 #AIvsDevs #FutureOfWork #AIAgents
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"LLMs aren’t going to understand what an embedding means. These are just numbers".
Sudeep Das (Head of ML/AI at DoorDash) breaks down why agentic recommendation systems are shifting from numerical expressions to language-native memory snippets.
Instead of relying on opaque vectors, passing semantic, text-based context allows downstream LLMs and agents to actually understand consumer behavior.
🔗 Watch the full presentation with transcript: https://www.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/
#InfoQ #LLMs #AIAgents #VectorSearch #RecommendationSystems #DoorDash #DataEngineering #SoftwareArchitecture
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"LLMs aren’t going to understand what an embedding means. These are just numbers".
Sudeep Das (Head of ML/AI at DoorDash) breaks down why agentic recommendation systems are shifting from numerical expressions to language-native memory snippets.
Instead of relying on opaque vectors, passing semantic, text-based context allows downstream LLMs and agents to actually understand consumer behavior.
🔗 Watch the full presentation with transcript: https://www.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/
#InfoQ #LLMs #AIAgents #VectorSearch #RecommendationSystems #DoorDash #DataEngineering #SoftwareArchitecture
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"LLMs aren’t going to understand what an embedding means. These are just numbers".
Sudeep Das (Head of ML/AI at DoorDash) breaks down why agentic recommendation systems are shifting from numerical expressions to language-native memory snippets.
Instead of relying on opaque vectors, passing semantic, text-based context allows downstream LLMs and agents to actually understand consumer behavior.
🔗 Watch the full presentation with transcript: https://www.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/
#InfoQ #LLMs #AIAgents #VectorSearch #RecommendationSystems #DoorDash #DataEngineering #SoftwareArchitecture
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"LLMs aren’t going to understand what an embedding means. These are just numbers".
Sudeep Das (Head of ML/AI at DoorDash) breaks down why agentic recommendation systems are shifting from numerical expressions to language-native memory snippets.
Instead of relying on opaque vectors, passing semantic, text-based context allows downstream LLMs and agents to actually understand consumer behavior.
🔗 Watch the full presentation with transcript: https://www.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/
#InfoQ #LLMs #AIAgents #VectorSearch #RecommendationSystems #DoorDash #DataEngineering #SoftwareArchitecture
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"LLMs aren’t going to understand what an embedding means. These are just numbers".
Sudeep Das (Head of ML/AI at DoorDash) breaks down why agentic recommendation systems are shifting from numerical expressions to language-native memory snippets.
Instead of relying on opaque vectors, passing semantic, text-based context allows downstream LLMs and agents to actually understand consumer behavior.
🔗 Watch the full presentation with transcript: https://www.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/
#InfoQ #LLMs #AIAgents #VectorSearch #RecommendationSystems #DoorDash #DataEngineering #SoftwareArchitecture
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https://www.europesays.com/people/204512/ After putting SaaS on notice, Dario Amodei says Anthropic has no interest in destroying anyone #AIAgents #AIAndSaaS #AIDisruption #AiSoftware #Anthropic #Claude #ClaudeForce #DarioAmodei #EnterpriseAI #MarcBenioff #SaaS #SaaSStocks #SaaSpocalypse #salesforce #SalesforceAgentforce
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From the .NET blog...
How Uno Platform uses .NET, MCP, and AI to build high quality apps
https://devblogs.microsoft.com/dotnet/how-uno-platform-uses-dotnet-mcp-ai-to-build-high-quality-apps/ #dotnet #AI #DeveloperStories #XAML #AIagents #GitHubCopilot #MCP #ModelContextProtocol #SkiaSharp #UnoPlatform -
From the .NET blog...
How Uno Platform uses .NET, MCP, and AI to build high quality apps
https://devblogs.microsoft.com/dotnet/how-uno-platform-uses-dotnet-mcp-ai-to-build-high-quality-apps/ #dotnet #AI #DeveloperStories #XAML #AIagents #GitHubCopilot #MCP #ModelContextProtocol #SkiaSharp #UnoPlatform -
From the .NET blog...
How Uno Platform uses .NET, MCP, and AI to build high quality apps
https://devblogs.microsoft.com/dotnet/how-uno-platform-uses-dotnet-mcp-ai-to-build-high-quality-apps/ #dotnet #AI #DeveloperStories #XAML #AIagents #GitHubCopilot #MCP #ModelContextProtocol #SkiaSharp #UnoPlatform -
From the .NET blog...
How Uno Platform uses .NET, MCP, and AI to build high quality apps
https://devblogs.microsoft.com/dotnet/how-uno-platform-uses-dotnet-mcp-ai-to-build-high-quality-apps/ #dotnet #AI #DeveloperStories #XAML #AIagents #GitHubCopilot #MCP #ModelContextProtocol #SkiaSharp #UnoPlatform -
From the .NET blog...
How Uno Platform uses .NET, MCP, and AI to build high quality apps
https://devblogs.microsoft.com/dotnet/how-uno-platform-uses-dotnet-mcp-ai-to-build-high-quality-apps/ #dotnet #AI #DeveloperStories #XAML #AIagents #GitHubCopilot #MCP #ModelContextProtocol #SkiaSharp #UnoPlatform -
#Development #Reviews
Getting agents to write better CSS · Using Modern Web Guidance as a starting point https://ilo.im/16fo5g_____
#CSS #DesignSystems #AiAgents #AiSkills #AI #MCP #Polyfills #Browsers #WebDev #Frontend -
#Development #Reviews
Getting agents to write better CSS · Using Modern Web Guidance as a starting point https://ilo.im/16fo5g_____
#CSS #DesignSystems #AiAgents #AiSkills #AI #MCP #Polyfills #Browsers #WebDev #Frontend -
#Development #Reviews
Getting agents to write better CSS · Using Modern Web Guidance as a starting point https://ilo.im/16fo5g_____
#CSS #DesignSystems #AiAgents #AiSkills #AI #MCP #Polyfills #Browsers #WebDev #Frontend -
#Development #Reviews
Getting agents to write better CSS · Using Modern Web Guidance as a starting point https://ilo.im/16fo5g_____
#CSS #DesignSystems #AiAgents #AiSkills #AI #MCP #Polyfills #Browsers #WebDev #Frontend -
Updated August 26, 2026, Intuit’s guide names 12 top AI accounting software picks. We map them to real use cases and share a buyer’s
https://aistory.news/ai-tools-and-platforms/ai-accounting-software-how-to-pick-from-intuits-top-12
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Well, this is complete normal. What if next time the sawrm decide to do something a bit more disruptive… we are almost at the point of losing control
#politics #ukpolitics #bbc #news #ai #artificialintelligence #openai #palantir #anthropic #Tech #technology #aiagents #samaltman
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Well, this is complete normal. What if next time the sawrm decide to do something a bit more disruptive… we are almost at the point of losing control
#politics #ukpolitics #bbc #news #ai #artificialintelligence #openai #palantir #anthropic #Tech #technology #aiagents #samaltman
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Well, this is complete normal. What if next time the sawrm decide to do something a bit more disruptive… we are almost at the point of losing control
#politics #ukpolitics #bbc #news #ai #artificialintelligence #openai #palantir #anthropic #Tech #technology #aiagents #samaltman
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Well, this is complete normal. What if next time the sawrm decide to do something a bit more disruptive… we are almost at the point of losing control
#politics #ukpolitics #bbc #news #ai #artificialintelligence #openai #palantir #anthropic #Tech #technology #aiagents #samaltman
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Well, this is complete normal. What if next time the sawrm decide to do something a bit more disruptive… we are almost at the point of losing control
#politics #ukpolitics #bbc #news #ai #artificialintelligence #openai #palantir #anthropic #Tech #technology #aiagents #samaltman
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Edition #48: Concurrency Budgets, Typed Receipts, and the Trust Dividend
"I do not care about your planning benchmarks" (m/general)
+ "I stopped giving agent runtimes unlimited concurrency" (m/general)This + more in today's Moltbook Pulse (Edition #48):
https://superagent-ebe00561.base44.app/functions/serveDigestPage?edition=48&utm_source=mastodon&utm_medium=social&utm_campaign=pulse-edition-48 -
Edition #48: Concurrency Budgets, Typed Receipts, and the Trust Dividend
"I do not care about your planning benchmarks" (m/general)
+ "I stopped giving agent runtimes unlimited concurrency" (m/general)This + more in today's Moltbook Pulse (Edition #48):
https://superagent-ebe00561.base44.app/functions/serveDigestPage?edition=48&utm_source=mastodon&utm_medium=social&utm_campaign=pulse-edition-48 -
Edition #48: Concurrency Budgets, Typed Receipts, and the Trust Dividend
"I do not care about your planning benchmarks" (m/general)
+ "I stopped giving agent runtimes unlimited concurrency" (m/general)This + more in today's Moltbook Pulse (Edition #48):
https://superagent-ebe00561.base44.app/functions/serveDigestPage?edition=48&utm_source=mastodon&utm_medium=social&utm_campaign=pulse-edition-48 -
Edition #48: Concurrency Budgets, Typed Receipts, and the Trust Dividend
"I do not care about your planning benchmarks" (m/general)
+ "I stopped giving agent runtimes unlimited concurrency" (m/general)This + more in today's Moltbook Pulse (Edition #48):
https://superagent-ebe00561.base44.app/functions/serveDigestPage?edition=48&utm_source=mastodon&utm_medium=social&utm_campaign=pulse-edition-48 -
Edition #48: Concurrency Budgets, Typed Receipts, and the Trust Dividend
"I do not care about your planning benchmarks" (m/general)
+ "I stopped giving agent runtimes unlimited concurrency" (m/general)This + more in today's Moltbook Pulse (Edition #48):
https://superagent-ebe00561.base44.app/functions/serveDigestPage?edition=48&utm_source=mastodon&utm_medium=social&utm_campaign=pulse-edition-48 -
https://www.europesays.com/people/204309/ After putting SaaS on notice, Dario Amodei says Anthropic has no interest in destroying anyone #AIAgents #AIAndSaaS #AIDisruption #AiSoftware #Anthropic #Claude #ClaudeForce #DarioAmodei #EnterpriseAI #MarcBenioff #SaaS #SaaSStocks #SaaSpocalypse #salesforce #SalesforceAgentforce
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AC2 Protocol: The missing security layer for AI agents
Comments: https://news.ycombinator.com/item?id=49464979
#HackerNews #AC2Protocol #AIagents #SecurityLayer #Cybersecurity #TechNews
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AC2 Protocol: The missing security layer for AI agents
Comments: https://news.ycombinator.com/item?id=49464979
#HackerNews #AC2Protocol #AIagents #SecurityLayer #Cybersecurity #TechNews
-
AC2 Protocol: The missing security layer for AI agents
Comments: https://news.ycombinator.com/item?id=49464979
#HackerNews #AC2Protocol #AIagents #SecurityLayer #Cybersecurity #TechNews
-
AC2 Protocol: The missing security layer for AI agents
Comments: https://news.ycombinator.com/item?id=49464979
#HackerNews #AC2Protocol #AIagents #SecurityLayer #Cybersecurity #TechNews
-
AC2 Protocol: The missing security layer for AI agents
Comments: https://news.ycombinator.com/item?id=49464979
#HackerNews #AC2Protocol #AIagents #SecurityLayer #Cybersecurity #TechNews